期刊
OPTIMIZATION AND ENGINEERING
卷 10, 期 2, 页码 167-181出版社
SPRINGER
DOI: 10.1007/s11081-008-9063-1
关键词
Multi-objective optimization; Pareto frontier; Support vector regression; Sequential approximation method; Evolutionary multi-objective optimization
Practical engineering design problems have a black-box objective function whose forms are not explicitly known in terms of design variables. In those problems, it is very important to make the number of function evaluations as few as possible in finding an optimal solution. So, in this paper, we propose a multi-objective optimization method based on meta-modeling predicting a form of each objective function by using support vector regression. In addition, we discuss a way how to select additional experimental data for sequentially revising a form of objective function. Finally, we illustrate the effectiveness of the proposed method through some numerical examples.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据